사물인터넷과 Amazon Web Services를 활용한 공간 혼잡도 측정 시스템 = Spatial Crowdedness Measurement System using IoT and Amazon Web Services

다국어 초록 (Multilingual Abstract)

In this paper, we conducted research on a spatial crowdedness measurement system using the Internet of Things(IoT) and Amazon Web Services(AWS). Current spatial congestion measurement systems require expensive servers and entail significant investment in algorithm development and updates to enhance spatial recognition performance. The proposed system can be implemented at low cost by capturing the screen of a web camera(or CCTV) through OpenCV on a small/low-cost single board computer, Raspberry Pi, and transmitting and processing the information to AWS. Within AWS, the received spatial image information is stored in Amazon S3(Amazon Simple Storage Service).
Subsequently, Amazon Lambda transfers the images to Amazon Rekognition for congestion analysis based on the images. The Amazon Rekognition service offers the capability to utilize artificial intelligence(AI) technology for image processing at a low cost of 0.001 dollars per image. Through human object recognition, it enables congestion analysis. The analyzed congestion level is stored in DB(Database), and the result is displayed on the screen. The proposed system is expected to be used for checking crowdedness at low cost in public place

참고문헌 (Reference)

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8 Intel, "OpenCV"

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10 Amazon, "Amazon Web Services S3"

11 Amazon, "Amazon Web Services Rekognition"

12 Amazon, "Amazon Web Services RDS"

13 Amazon, "Amazon Web Services Lambda"

14 Amazon, "Amazon Web Services"

15 J. G. Kim, "A Study on the Congestion Measurement System of Public Transportation Using CCTV" 25 (25): 25-27, 2022